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Gomez-Casero, M
Anastasiou, E
Mzuku, M
Murphy, J.M
POLEPOLE, S.J
Post, S
Pannell, D
Canal Filho, R
Chung, S
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Authors
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Gomez-Casero, M
Pe, J.M
Jurado-Exp, M
Lopez-Granados, F
Castillejo-Gonz, I
Garc, A
Mzuku, M
Khosla, R
Reich, R
http://icons.paqinteractive.com/16x16/ac, G
Smith, F
MacDonald, L
WORTH, S.H
POLEPOLE, S.J
Fountas, S
Kotseridis, Y
Balafoutis, A
Anastasiou, E
Koundouras, S
Kallithraka, S
Kyraleou, M
Cho, W
Kim, D
Kang, C
Kim, H
Son, J
Chung, S
Jiang, J
Yun, H
Pannell, D
Weersink, A
Gandorfer, M
Post, S
Jermy, M
Gaynor, P
Kabaliuk, N
Werner, A
Tasissa, A
Li, L
Murphy, J.M
Balboa, G
Masnello, J.C
De Oliveira Moreira, F
Canal Filho, R
Da Silva, E.R
Molin, J.P
Topics
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Site-Specific Nutrient, Lime and Seed Management
Precision Crop Protection
Artificial Intelligence (AI) in Agriculture
Demonstration
Type
Oral
Poster
Year
2010
2014
2016
2018
2024
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Filter results9 paper(s) found.

1. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea Crop

  The software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc

2. Spatial Variability Of Measured Soil Properties Across Site- Specific Management Zones

The spatial variation of productivity across farm fields can be classified by delineating site-specific management zones. Since productivity is influenced by soil characteristics, the spatial pattern of productivity could be caused by a corresponding variation in certain soil properties. Determining the source of variation in productivity can help achieve more effective site-specific management, the objectives of this study were (i) to characterize the spatial variability of soil physical properties... M. Mzuku, R. Khosla, R. Reich, G. Http://icons.paqinteractive.com/16x16/ac, F. Smith, L. Macdonald

3. Analyzing Organic Farming Training In The Curriculum Of The University Of Kwazulu-Natal, Pietermaritzburg

  ANALYZING ORGANIC FARMING TRAINING IN THE CURRICULUM OF THE UNIVERSITY OF KWAZULU-NATAL, PIETERMARITZBURG      SJ, Polepole * and SH, Worth        Agricultural Extension and Rural Resource Management Program;      University of KwaZulu-Natal; School... S.H. Worth, S.J. Polepole

4. Site-Specific Variability Of Grape Composition And Wine Quality

Precision Viticulture (PV) is the application of site-specific tools to delineate management zones in vineyards for either targeting inputs or harvesting blocks according to grape maturity status. For the creation of management zones, soil properties, topography, canopy characteristics and grape yield are commonly measured during the growing season. The majority of PV studies in winegrapes have focused on the relation of soil and vine-related spatial data with grape composition... S. Fountas, Y. Kotseridis, A. Balafoutis, E. Anastasiou, S. Koundouras, S. Kallithraka, M. Kyraleou

5. Precision Nutrient Management System Based on Ion and Crop Growth Sensing

Automated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun

6. Flat Payoff Functions and Site-Specific Crop Management

Within the neighbourhood of any economically “optimal” management system, there is a set of alternative systems that are only slightly less attractive than the optimum. Often this set is large; in other words, the payoff function is flat within the vicinity of the optimum. This has major implications for the economics of variable-rate site-specific crop management. The flatter the payoff function, the lower the benefits of precision in the adjustment of input rates spatially within... D. Pannell, A. Weersink, M. Gandorfer

7. Real-Time Control of Spray Drop Application

Electrostatic application of spray drops provides unique opportunities to precisely control the application of pesticides due to the additional electrostatic force on the spray drops, in addition to the normally seen forces of aerodynamic drag, gravity, and inertia. In this work, we develop a computational model to predict the spray drop trajectories. The model is validated through experiments with high speed photography of spray drop trajectories, and quantification of which trajectories lead... S. Post, M. Jermy, P. Gaynor, N. Kabaliuk, A. Werner

8. Sparse Coding for Classification Via a Locality Regularizer: with Applications to Agriculture

High-dimensional data is commonly encountered in various applications, including genomics, as well as image and video processing. Analyzing, computing, and visualizing such data pose significant challenges. Feature extraction methods become crucial in addressing these challenges by obtaining compressed representations that are suitable for analysis and downstream tasks. One effective technique along these lines is sparse coding, which involves representing data as a sparse linear combination of... A. Tasissa, L. Li, J.M. Murphy

9. Sugarcane Yield Mapping Using an On-board Volumetric Sensor

Few alternatives are available to the sugarcane sector for monitoring crop productivity. However, in recent years, research has been dedicated to developing methods ranging from estimation based on engine parameters to using sensors and artificial intelligence. This study aims to present a new tool for monitoring productivity applied to sugarcane cultivation, which utilizes a volumetric optical sensor, in contrast to other methods already used for this measurement, and is recently being introduced... G. Balboa, J.C. Masnello, F. De oliveira moreira, R. Canal filho, E.R. Da silva, J.P. Molin